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Technical Reference🔗

The PlanktoScope is a modular, open-source platform for high-throughput quantitative imaging of plankton samples. Its small size, ease of use, and low cost make it suitable for a variety of applications, including the monitoring of laboratory cultures or natural micro-plankton communities. It can be controlled from any WiFi-enabled device and can be easily reconfigured to meet the changing needs of the user.

Key Features🔗

Here are some key features of the PlanktoScope:

  1. Low cost: The PlanktoScope is designed to be affordable, with parts costing under $1000.
  2. Modular: The PlanktoScope is modular, meaning it can be easily reconfigured to meet the changing needs of users.
  3. Open-source: The PlanktoScope is based on open-source hardware and software, making it accessible to a wide community of engineers, researchers, and citizens.
  4. Versatility: The PlanktoScope is versatile, and can be used to study a variety of plankton types, including laboratory cultures and natural micro-plankton communities.
  5. High-throughput: The PlanktoScope is capable of high-throughput quantitative imaging, allowing users to analyze large numbers of samples quickly and efficiently.
  6. WiFi-enabled: The PlanktoScope can be controlled from any WiFi-enabled device, making it easy to use and deploy in a variety of settings.
  7. Portable: The PlanktoScope is small and portable, making it easy to transport and use in the field.
  8. Ease of use: The PlanktoScope is designed to be easy to use, with instructions for assembly and use available on the PlanktoScope website.

Device specification🔗



  • height: 105 mm
  • wide: 275 mm
  • depth: 125 mm


  • 4 Core ARM-Cortex-A72 Processor with 1,50 GHz
  • 4 GB Arbeitsspeicher (depending on the purchased version)
  • 64 GB Flash memory (depending on the purchased version)
  • Sony IMX477R Image sensor with 12.3MP
  • M12 mount optics with 16 and 25 mm lenses
  • Automatic focus via linear guide
  • automatic sampling via peristaltic pump
  • the case is made of wood fiberboard


  • Debian based Embedded Linux operating
  • Node-Red based user interface
  • Python Image processing service and cloud connection


  • Focus stage control
  • Pump control
  • Automatic image capture
  • Automatic segmentation, optimization and object detection
  • Control via smartphone or tablet

Areas of Application🔗

  • Plankton analysis of small animals and algae living in water
  • Mobile use via external power supply

System Requirements🔗

  • a Web-Browser to control the device (like a Notebook, Smartphone or Tablet)